Back
For best output, select "Paper Size" as "A4" and "Margin" as "0" or "None".
To save or print to PDF, please select Print Destination > Save as PDF, enable Background Graphics under "More Settings", then click "Save".
During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
In chronic kidney disease, sarcopenia causes diverse clinical problems and vice versa. Sarcopenia is defined as a reduction in muscle mass and quality, accompanied by a decline in physical performance, and it is difficult to comprehensively evaluate it in actual situations. Therefore, muscle mass measurement is used first currently. While artificial intelligence is being actively applied to diagnosis, interpretation, and treatment planning in various diseases, we compared non-contrast computed tomography (CT) integrated with artificial intelligence (AI) solutions with existing sarcopenia diagnostic methods.
We collected the demographic characteristics, renal function including serum creatinine and dialysis status, and mortality in outpatients or inpatients who had a history of visits nephrology clinic between January 2010 and June 2025. These patients underwent dual-energy X-ray absorptiometry (DXA) and abdominal CT scans within 6-month interval. A single-center retrospective study.
Of a total of 366 patients (180 men, 186 women), 249 patients were diagnosed with sarcopenia with DXA. The median follow-up period was 55.5 months; 29 deaths and 26 dialysis-dependent end-stage kidney disease patients occurred during that time. The mean glomerular filtration rate using the 2021 CKD-EPI formula was 90.3 ml/min/1.73m2. AI-driven total skeletal muscle volume and height-adjusted adhesive muscle mass using DXA showed a significant correlation (Spearman's rho = 0.67, p-value <0.01). Specifically, when the cutoff value was divided into two groups with 1750 cm2, the Receiver Operating Characteristic (ROC) curve showed significant levels of mortality predictive power of sarcopenia with DXA (DXA ROC 0.702, p = 0.01, AI ROC 0.73, p = 0.02) The total skeletal muscle volume also has statistical significance predicting mortality (multivariate Cox regression, HR -0.998 [95% CI 0.996-0.999], p-value 0.01).
This study evaluated whether an AI-based approach utilizing CT scans could serve as a viable alternative to DXA. The findings confirmed that the AI solution can effectively predict both sarcopenia and mortality. In the era of advanced radiomics, AI technologies hold promise for delivering maximal diagnostic information to clinicians with minimal risk to patients.
